Jobs Companies Modeln Business Intelligence Data Analytics Engineer (Snowflake, Fivetran)

À propos de ce poste Business Intelligence Data Analytics Engineer (Snowflake, Fivetran) chez Modeln

Modeln · Sur site · Hyderabad India
We are seeking a Business Intelligence & Analytics Engineer to join our Business Intelligence team. This role partners closely with Finance and cross-functional teams to build and maintain the data infrastructure, pipelines, and reporting layer that power financial planning, forecasting, and performance management. The ideal candidate is comfortable working across the full data stack—from ingestion and transformation to visualization—and brings strong analytical judgment alongside technical depth. 

Job Responsibilities

  • Design, build, and maintain scalable data pipelines using Fivetran to ingest data from Salesforce, ERP, and other business systems into Snowflake. 

  • Own the data transformation layer between raw ingested sources and analytics-ready datasets, ensuring models are clean, tested, documented, and aligned to Finance and GTM reporting needs. 

  • Build and maintain Tableau dashboards and reporting assets to track key financial and go-to-market metrics, including pipeline coverage, ARR/NRR, revenue retention, quota attainment, and other GTM activities. 

  • Partner with Finance and cross-functional stakeholders to translate business questions into data models, metrics definitions, and dashboard solutions. 

  • Validate data accuracy and reconcile financial and operational metrics across source systems (CRM, ERP, and other systems of record) and the Snowflake data warehouse. 

  • Manage data warehouse objects in Snowflake, including schema design, virtual warehouse configuration, role-based access controls, and query optimization. 

  • Define and enforce KPI definitions, data source documentation, and metric governance to drive consistent reporting across Finance and GTM teams. 

  • Analyze customer, revenue, and product usage data to surface trends related to growth, churn, expansion, pricing, and performance. 

  • Continuously improve analytics workflows, documentation standards, and self-service reporting capabilities to scale insight delivery across the organization. 

Job Qualification

  • 4–7 years of experience in analytics engineering, business intelligence, or a related data role. 

  • Hands-on experience with Snowflake and Fivetran in a production environment. 

  • Strong SQL skills for querying, joining, and transforming structured data across complex schemas. 

  • Experience building and maintaining Tableau dashboards and data sources. 

  • Familiarity with CRM data structures, particularly Salesforce objects and reporting. 

  • Experience working cross-functionally with Finance, Ops, or GTM teams to support data and reporting needs. 

  • Bachelor’s degree in a quantitative, technical, or business fields (e.g., Statistics, Mathematics, Economics, Computer Science, Data Science, Business Analytics). Master’s degree preferred. 

 Technical Skills 

  • Snowflake: schema design, virtual warehouse management, RBAC, query optimization, and cost monitoring. 

  • Fivetran: connector configuration, sync scheduling, schema change handling, and MAR management. 

  • Tableau: advanced dashboard design, calculated fields, LOD expressions, data source management, and Tableau Server/Cloud publishing. 

  • SQL: advanced querying across Snowflake; window functions, CTEs, and performance tuning. 

  • Salesforce: familiarity with standard and custom objects, SFDC data exports, and CRM reporting structures. 

  • Git: version control for analytics codebases. 

  • Python (preferred) for data analysis, automation, and supplemental data processing tasks. 

 Analytical & Business Acumen 

  • Solid understanding of SaaS business metrics (ARR, NRR, churn, pipeline coverage, quota attainment) and how they flow through financial and GTM reporting. 

  • Ability to integrate, clean, and analyze data from disparate source systems into a coherent, governed data model. 

  • Skilled in translating complex data into clear narratives, actionable insights, and strategic recommendations for Finance and executive audiences. 

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